Receiver and method for equalizing signals

ABSTRACT

A receiver and a method for equalizing signals, the method includes: receiving input signals; sampling the input signals to provide oversampled samples; processing the oversampled samples to provide symbol spaced samples and to provide fractionally spaced samples that represent the oversampled samples; calculating taps of a fractionally spaced equalizer based on the symbol spaced samples; feeding the taps to the fractionally spaced equalizer; and filtering the fractionally spaced samples by the fractionally spaced equalizer to provide equalized samples.

FIELD OF THE INVENTION

This invention relates to a receiver and a method for equalizingsignals.

BACKGROUND OF THE INVENTION

In modern communication transmitter digital information is converted toanalog information and then transmitted over a channel. The digitalinformation can include a sequence of samples that is provided at asymbol rate, i.e. adjacent samples are spaced apart by a symbol period.

In Code Division Multiple Access (CDMA) communication systems, thissequence of samples is referred to as a chip sequence and the rate withwhich the chips of the chip sequence are is called a chip rate. Thus,adjacent chips are said to be spaced apart by a chip period.

In CDMA communication systems the chip sequence is pulse-shaped by apulse shaping filter (such as a Root Raised Cosine filter) to providepulse shaped signals. The pulse shaped signals are transmitted over amedium (such as a multipath fading channel).

The pulse shaping can widen the spectrum of the chip sequence. Noise canbe added to the transmitted pulsed shaped signals and timing errors canbe introduced to the transmitted pulsed shaped signals.

A receiver can include one or more input antennas for receiving thetransmitted pulsed shaped signals. The transmitted pulsed shaped signals(as well as added noise) can be regarded as input signals of thereceiver. The input signals are filtered by one or more front end filterof the receiver, sampled to provide input signal samples and then sentto an equalizer.

The equalizer outputs equalized samples that can be further processed bythe receiver. The additional processing can include descrambling,de-spreading, decoding and the like.

Linear equalizers based on minimum square error (LMMSE) criterion wererecently adopted as baseline equalizers for Code Division MultipleAccess (CDMA) based on third generation (3G) communication networks.

There are two families of LMSSE equalizers—fractionally spacedequalizers and symbol spaced equalizers.

In non-CDMA communication systems fractionally spaced equalizers receiveoversampled input signal samples—input signal samples that were obtainedby sampling the input signals at a sampling rate that is higher than thesymbol rate. Adjacent oversampled input samples are spaced apart by afraction of the symbol period.

In CDMA communication systems fractionally spaced equalizers receiveoversampled input signal samples—input signal samples that were obtainedby sampling the input signals at a sampling rate that is higher than thechip rate. Adjacent oversampled input samples are spaced apart by afraction of the chip period.

In CDMA communication systems the taps of fractionally spaced equalizersare spaced apart by a fraction of the chip period of the chip sequence.In non-CDMA communication systems the taps of fractionally spacedequalizers are spaced apart by a fraction of the symbol period. Theoversampling fulfills the Nyquist criterion and fractionally spacedequalizers are therefore insensitive to the sampling time at thereceiver.

One drawback of fractionally spaced equalizer is their complexity andtheir high power consumption.

In non-CDMA communication systems symbol spaced equalizers receivesymbol rate samples of the received input signal. The taps of symbolspaced equalizers are spaced apart by the symbol period.

In CDMA communication systems symbol spaced equalizers receive chip ratesamples of the received input signal. The taps of chip spaced equalizersare spaced apart by the chip period.

Due to the pulse shaping applied by the transmitter the sampling doesnot fulfill the Nyquist criterion and symbol spaced equalizers aresensitive to the sampling time at the receiver.

In contrary to fractionally spaced equalizers, symbol spaced equalizersare simple and their power consumption is relatively low.

SUMMARY OF THE INVENTION

The present invention provides a method and a receiver as described inthe accompanying claims.

Specific embodiments of the invention are set forth in the dependentclaims.

These and other aspects of the invention will be apparent from andelucidated with reference to the embodiments described hereinafter.

BRIEF DESCRIPTION OF THE DRAWINGS

Further details, aspects and embodiments of the invention will bedescribed, by way of example only, with reference to the drawings. Inthe drawings, like reference numbers are used to identify like orfunctionally similar elements. Elements in the figures are illustratedfor simplicity and clarity and have not necessarily been drawn to scale.

FIG. 1 schematically shows a block diagram of an example of anembodiment of a receiver;

FIG. 2 schematically shows a block diagram of an example of anembodiment of a receiver;

FIG. 3 schematically shows a block diagram of an example of anembodiment of calculator and of a fractionally spaced equalizer;

FIG. 4 schematically shows a flow-chart of an example of a method forequalizing signals;

FIG. 5 schematically shows graphs that illustrate an example of resultsof a simulation that evaluated different equalization algorithms;

FIG. 6 schematically shows graphs that illustrate an example of resultsof another simulation that evaluated different equalization algorithms;and

FIG. 7 schematically shows graphs that illustrate an example of resultsof a further simulation that evaluated different equalizationalgorithms.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

In the following specification, the invention will be explained withreference to specific examples of embodiments of the invention. It will,however, be evident that various modifications and changes can be madetherein without departing from the broader spirit and scope of theinvention as set in the appended claims.

Because the described examples may, for the most part, be implementedusing electronic components and circuits known to those skilled in theart, details will not be explained in any greater extent than thatconsidered necessary, for the understanding and appreciation of theunderlying concepts of the present invention and in order not toobfuscate or distract from the teachings of the present invention.

At least some of the stages of the method illustrated below and at leastsome units or components of the receiver illustrated below can also beimplemented in a computer program for running on a computer system. Atleast some of the stages of the method illustrated below can be executedby executing code portions when run on a programmable apparatus, such asa computer system or enabling a programmable apparatus to performfunctions of a receiver according to the invention. For example, variousfilters, time domain to frequency domain converters, processing stagesexecuted by the processing unit, and calculation performed by thecalculator of the receiver can be implemented by software.

A computer program is a list of instructions such as a particularapplication program and/or an operating system. The computer program canfor instance include one or more of: a subroutine, a function, aprocedure, an object method, an object implementation, an executableapplication, an applet, a servlet, a source code, an object code, ashared library/dynamic load library and/or other sequence ofinstructions designed for execution on a computer system.

The computer program can be stored internally on computer readablestorage medium or transmitted to the computer system via a computerreadable transmission medium. All or some of the computer program can beprovided on computer readable media permanently, removably or remotelycoupled to an information processing system. The computer readable mediacan include, for example and without limitation, any number of thefollowing: magnetic storage media including disk and tape storage media;optical storage media such as compact disk media (e.g., CD-ROM, CD-R,etc.) and digital video disk storage media; nonvolatile memory storagemedia including semiconductor-based memory units such as FLASH memory,EEPROM, EPROM, ROM; ferromagnetic digital memories; MRAM; volatilestorage media including registers, buffers or caches, main memory, RAM,etc.; and data transmission media including computer networks,point-to-point telecommunication equipment, and carrier wavetransmission media, just to name a few.

A computer process typically includes an executing (running) program orportion of a program, current program values and state information, andthe resources used by the operating system to manage the execution ofthe process. An operating system (OS) is the software that manages thesharing of the resources of a computer and provides programmers with aninterface used to access those resources. An operating system processessystem data and user input, and responds by allocating and managingtasks and internal system resources as a service to users and programsof the system.

The computer system can for instance include at least one processingunit, associated memory and a number of input/output (I/O) devices. Whenexecuting the computer program, the computer system processesinformation according to the computer program and produces resultantoutput information via I/O devices.

In the following specification, the invention has been described withreference to specific examples of embodiments of the invention. It will,however, be evident that various modifications and changes can be madetherein without departing from the broader spirit and scope of theinvention as set forth in the appended claims.

A method and a receiver for equalizing signals are provided. The methodand the receiver utilize an equalization algorithm that has aperformance comparable to fractionally spaced equalization andcomplexity comparable to symbol spaced equalization.

The equalization algorithm includes: (a) sampling input signals toprovide oversampled samples; (b) processing the oversampled samples toprovide symbol spaced symbols and fractionally spaced samples; (c)calculating taps of a fractionally spaced equalizer based on the symbolspaced samples; (d) feeding the taps to the fractionally spacedequalizer, and (e) filtering the fractionally spaced samples by thefractionally spaced equalizer to provide equalized signals.

The method and receiver benefit from performing calculation in thefrequency domain, by interpolating autocorrelation results andcross-correlation results (instead of interpolating the oversampledsamples), by applying anti-aliasing filtering and by ignoring some ofthe cross-correlation results due to redundancies introduced by theanti-aliasing filtering.

The interpolation of the autocorrelation results and cross-correlationresults reduces the complexity of the equalization algorithm, as can beillustrated by the following example: the oversampled samples caninclude 1280 samples while the auto-correlation results can include 189elements. The low number of auto-correlation elements can be partiallycontributed to the anti-aliasing that facilitates ignoring variouselements of the auto-correlation. Interpolating the 189 elements is moreefficient than interpolating the 1280 fractionally spaced samples.

The following description refers to non-CDMA communication systems suchas but not limited to Time Division Multiplex Access (TDMA)communication systems. However, the following description can be appliedto CDMA communication systems as well. The terms “symbol” as used inrelation to a non-CDMA communication system is within the context ofCDMA referred to as “chip” and accordingly when applying the presentspecification to CDMA systems, instead of the term “symbol” the term“chip” should be read. For example, the term “symbol spaced samples”should be replaced by “chip spaced samples”.

In a CDMA communication system the term “fractionally spaced” refers toa fraction of a chip period. For example, a fractionally spacedequalizer is an equalizer that is defined by taps that are spaced apartfrom each other by a fraction of a chip period. Yet for another example,fractionally spaced samples are samples that are spaced apart by afraction of a chip period.

FIG. 1 schematically shows a block diagram of an example of anembodiment of a receiver 10. The receiver 10 includes an input antenna20, a sampling unit such as an analog to digital converter (ADC) 30, aprocessing unit 40, a calculator 50, a fractionally spaced equalizer 60and additional components such as a descrambling/de-spreading filter 70and a decoder 72.

The input antenna 20 is connected to the ADC 30. The ADC 30 is connectedto the processing unit 40. The processing unit 40 is also connected tothe calculator 50 and to the fractionally spaced equalizer 60. Thefractionally spaced equalizer 60 is connected to thedescrambling/de-spreading filter 70. The descrambling/de-spreadingfilter 70 is connected to the decoder 72.

The input antenna 20 receives an input signal 110 and sends it to theADC 30. The ADC 30 samples the input signal 110 with an oversamplingratio V to provide oversampled samples 120. The oversampled samples 120are spaced apart from each other by a fraction of a sample period.

The oversampled samples 120 represent multiple (L) diversity branches.The number (L) of diversity branches equals the oversampling ratio (V)multiplied by the number (S) of input antennas (such as the inputantenna 20) that receive the input signal. In mathematical terms L=V*S.

The diversity branches are processed by the receiver 10 in order todetermine the content of the chip sequence that was pulsed shaped,transmitted over a channel and received by the receiver 10.

The oversampled samples 120 are sent from the ADC 30 to the processingunit 40. The processing unit 40 processes the oversampled samples 120 toprovide the fractionally spaced samples 130 and to provide the symbolspaced samples 150. The symbol spaced samples 150 are sent from theprocessing unit 40 to the calculator 50. The fractionally spaced samples130 are sent to the fractionally spaced equalizer 60.

The fractionally spaced samples 130 are spaced apart by a fraction ofthe symbol period. The sample spaced samples 150 are spaced apart by asample period.

The symbol spaced samples 150 and the fractionally spaced samples 130represent the oversampled samples 120—as the symbol spaced samples 150and the fractionally spaced samples 130 convey information thatrepresents at least a portion of the content of the oversampled samples120.

Each of the symbol spaced samples 150 and the fractionally spacedsamples 130 can represent one or multiple diversity branches.

The processing unit 40 of FIG. 1 does not include an anti-aliasingfilter—it generates the fractionally spaced samples 130 withoutperforming anti-aliasing filtering.

The processing unit 40 can, for example, apply a matched filteringprocess, perform a time domain to frequency domain conversion (such asFast Fourier Transform), perform a down-conversion, and the like.

The processing unit 40 includes an input filter 41, a time domain tofrequency domain converter such as a Fast Fourier Transform (FFT) unit44 and a decimation unit 42 that are serially connected to each other.The FFT unit 44 is connected between the input filter 41 and thedecimation unit 42.

The input filter 41 can, for example, be a matched filter, a selectivityfilter, and the like. The input filter outputs filtered samples to theFFT unit 44. The FFT unit 44 applies a time domain to frequency domainconversion on the filtered samples to provide the fractionally spacedsamples 130.

The decimation unit 42 decimates (down-samples) the fractionally spacedsamples 130 to provide the symbol spaced samples 150. The calculator 50receives the symbol spaced samples 150 and calculates taps (denoted 168)of the fractionally spaced equalizer 60 based on the symbol spacedsamples 150. The calculator 50 also feed the taps 168 to thefractionally spaced equalizer 60.

The calculator 50 includes a first calculation unit 51, a secondcalculation unit 52, an interpolation unit 54 and a third calculationunit 53.

The first calculation unit 51 receives the symbol spaced samples 150 andcalculates a symbol spaced autocorrelation 152 of the symbol spacedsamples 150. This can involve performing autocorrelation of diversitybranches and performing cross correlation of different diversitybranches.

The second calculation unit 52 receives the symbol spaced samples 150and a pilot sequence 154. The second calculation unit 52 calculates asymbol spaced channel estimation 156 by performing a cross correlationbetween the symbol spaced samples 150 and the pilot sequence 154.

The interpolation unit 54 receives the symbol spaced autocorrelation 152and interpolates it to provide a fractionally spaced autocorrelation162. The interpolation unit 54 also receives the symbol spaced channelestimation 156 and interpolates it to provide a fractionally spacedchannel estimation 166.

The interpolation unit 54 can perform an interpolation by applying aninterpolation filter that can be represented by a vector w. Vector w canbe defined as a truncated sinc series.

The n'th element (w(n)) of the vector w can be mathematicallyrepresented by the following equation:w(n)=[Sinus((n+0.5)*T)]/((n+0.5)*T)=Sinc((n+0.5)*T). The variable T isthe sample period of the input signal 110 or of the chip sequence.

Alternatively, the interpolation unit 54 can perform the interpolationusing any other interpolation method.

The third calculation unit 53 receives the fractionally spacedautocorrelation 162 and the fractionally spaced channel estimation 166.The third calculation unit 53 calculates the taps 168 of thefractionally spaced equalizer 60 based on the fractionally spacedautocorrelation 162 and the fractionally spaced channel estimation 166.

The third calculation unit 53 can perform at least one of the followingoperations or a combination thereof: averaging, circulant extension,FFT, matrix inversion, multiplication, inverse FFT (IFFT). Some of theseoperations will be illustrated in greater details in relation to FIG. 3.

The third calculation unit 53 outputs (feeds) the taps 168 of thefractionally spaced equalizer 60 or values that can be FFT converted orIFFT converted to provide the taps.

The fractionally spaced equalizer 60 performs a fractional spacedequalization by performing a sequence of multiplication and additionoperations. The fractionally spaced equalizer 60 performs theequalization after its taps are set to values that are based on the taps168 that are calculated by the third calculation unit 53.

The fractionally spaced equalizer 60 outputs equalized signals 170 thatcan be further processed by the receiver 10. For example, the equalizedsignals 170 can be filtered by the descrambling/de-spreading unit 70,decoded by the decoder 72, and the like.

FIG. 2 schematically shows a block diagram of an example of anembodiment of a receiver 10′. The receiver 10′ includes input antennas20 and 20′, an ADC 30, an ADC 30′, a processing unit 40′, a calculator50, a fractionally spaced equalizer 60 and additional components such asa descrambling/de-spreading unit 70 and a decoder 72.

The receiver 10′ of FIG. 2 differs from the receiver 10 of FIG. 1 by thefollowing: (i) receiver 10′ includes a pair of input antennas 20 and 20′(instead of a single input antenna 20), (ii) receiver 10′ includes apair of ADCs 30 and 30′ (instead of a single ADC 30), and (iii) receiver10′ includes anti-aliasing filters 43 and 43′. The anti-aliasing filters43 and 43′ belong to the processing unit 40′.

The input antenna 20 is connected to the ADC 30 and the input antenna20′ is connected to the ADC 30′.

The input antenna 20 receives the input signal 110. The ADC 30 generatesthe oversampled samples 120. The input antenna 20′ receives the inputsignal 110′. The ADC 30′ generates the oversampled samples 120′.

The oversampled samples 120 represent a plurality (V) of diversitybranches. The oversampled samples 120′ represent another plurality (V)of diversity branches. If V=2, receiver 10′ processes four diversitybranches.

The oversampled samples 120 and the oversampled samples 120′ are sent tothe processing unit 40′.

The processing unit 40′ processes the oversampled samples 120 and 120′to provide the fractionally spaced samples 130, the fractionally spacedsamples 130′, the symbol spaced samples 150 and the symbol spacedsamples 150′.

The processing unit 40′ includes: (i) input filters 41 and 41′, (ii)anti-aliasing filters 43 and 43′, (iii) decimation units 42 and 42′, and(iv) FFT units 44 and 44′. The processing unit 40′ processes, whenoperational, the oversampled samples 120 and 120′ by at least one of thefollowing operations: applying a matched filter, performing a timedomain to frequency domain conversion (such as Fast Fourier Transform),anti-aliasing filtering, down-conversion, and the like.

The anti-aliasing filter 43 is connected between the FFT unit 44 and thedecimation unit 42. The anti-aliasing filter 43′ is connected betweenthe FFT unit 44′ and the decimation unit 42′.

Each of the input filters 41 and 41′ can, for example, be a matchedfilter, a selectivity filter, and the like.

The input filters 41 and 41′ filter the oversampled samples 120 and 120′to provide filtered fractionally spaced samples 121 and 121′.

The FFT units 44 and 44′ perform a time to frequency domain conversionon the filtered fractionally spaced samples 121 and 121′ to provideintermediate fractionally spaced samples 122 and 122′.

The anti-aliasing filters 43 and 43′ perform anti-aliasing filtering ofthe intermediate fractionally spaced samples 122 and 122′ to providefractionally spaced samples 130 and 130′.

Each anti-aliasing filter out of 43 and 43′ can have a time responsethat is substantially equal to the symbol period of the chip sequence orof the input signals 110 or 110′. Each anti-aliasing filter out of 43and 43′ can be, for example, a simple truncated “sinc” filter based onthat symbol period.

The ADC 30 and the anti-aliasing filter 43 can be integrated together.Also the ADC 30′ and the anti-aliasing filter 43′ can be integratedtogether

The decimation units 42 and 42′ decimate (down-sample) the fractionallyspaced samples 130 and 130′ to provide symbol spaced samples 150 and150′.

The symbol spaced samples 150 and 150′ are sent from the processing unit40′ to the calculator 50. The fractionally spaced samples 130 and 130′are sent to the fractionally spaced equalizer 60.

The symbol spaced samples 150 and the fractionally spaced samples 130represent the oversampled samples 120, whilst the symbol spaced samples150′ and the fractionally spaced samples 130′ represent the oversampledsamples 120′.

The calculator 50 receives the symbol spaced samples 150 and 150′ andcalculates the taps of the fractionally spaced equalizer 60 based on thesymbol spaced samples 150 and 150′.

The First calculation unit 51 receives the symbol spaced samples 150 and150′, and calculates a symbol spaced autocorrelation 152 of the symbolspaced samples 150 and 150′. The calculation can involve, for example,performing autocorrelation of diversity branches and performing crosscorrelation of different diversity branches.

The second calculation unit 52 receives the symbol spaced samples 150and 150′ and a pilot sequence 154. The second calculation unitcalculates a symbol spaced channel estimation 156 by performing a crosscorrelation between each of symbol spaced samples 150 and 150′ andbetween the pilot sequence 154. The pilot sequence 154 can be providedfor each diversity branch. The pilot sequence 154 can be FFT convertedby an FFT that is not shown in either of the figures.

The interpolation unit 54 receives the symbol spaced autocorrelation 152and interpolates it to provide the fractionally spaced autocorrelation162. The interpolation unit 54 also receives the symbol spaced channelestimation 156 and interpolates it to provide the fractionally spacedchannel estimation 166.

The third calculation unit 53 receives the fractionally spacedautocorrelation 162 and the fractionally spaced channel estimation 166and calculates the taps 168 of the fractionally spaced equalizer 60based on the fractionally spaced autocorrelation 162 and thefractionally spaced channel estimation 166.

The third calculation unit 53 can perform at least one of the followingoperations or a combination thereof: averaging, circulant extension,FFT, matrix inversion, multiplication, IFFT and the like.

The fractionally spaced equalizer 60 performs fractional spacedequalization by performing a sequence of multiplication and additionoperations. The fractionally spaced equalizer 60 performs theequalization after its taps are set to values that are based on (orequal to) taps 168 that were calculated by the third calculation unit53.

The fractionally spaced equalizer 60 outputs equalized signals 170.

FIG. 3 schematically shows an example of a calculator 50 and of afractionally spaced equalizer 60.

The calculator 50 performs various calculations such as matrixtransforms, FFT, IFFT as well as additional mathematical operations thatsimplify the equalizing process and especially simplify the calculationof taps of the fractionally spaced filter 60.

The fractionally spaced filter 60 can, for example, be a half symbolspaced filter although other fractionally spaced filters ( 1/3, 1/4,1/8, and the like) can be included in the receiver 10 or 10′.

The manner in which the calculator 50 and the fractionally spacedequalizer 60 operate will be illustrated by using the followingnotations:

-   -   bold face letters represent vectors.    -   capital letters represent matrices.    -   v″ is the flipped and conjugated version of a vector v.    -   v^(T) is the transposed version of the vector v.    -   M^(T) is the transposed version of a matrix M.    -   M⁻¹ is the inverse matrix of M.    -   diag(a) is a diagonal matrix with a in its main diagonal.    -   F_(nm) is a Fourier transform matrix with dimensions of n×m.    -   x is a vector that its elements are the symbol spaced samples        150.    -   x_(i) is a vector that its elements belong to the i'th diversity        branch of the symbol spaced samples 150.    -   p is a vector that its elements form a pilot sequence.    -   g is a cross-correlation vector between p and x^(H) (g=x^(H)*p).    -   R is a covariance matrix that represents symbol spaced        autocorrelation 160. R=E (x*x^(H)).    -   f is a vector that its elements are the taps of fractionally        spaced filter 60. It can be calculated by using the following        linear minimum mean square error (LMMSE) criterion: f=R⁻¹*g.    -   w is an interpolation filter vector that represents the        interpolation unit 53, wherein w_(n)=Sinc ((n+1/S)*T).    -   Θ represents a convolution operation.

The first calculation unit 51 includes a multiplier 512 that is followedby the IFFT unit 514.

The First calculation unit 51 receives symbol spaced samples 150 and150′ and calculates a symbol spaced autocorrelation 152 that isrepresented by the covariance matrix R.

The multiplier 512 receives vectors that represent the symbol spacedsamples 150 and 150′, multiplies corresponding elements of these vectorsto provide a symbol spaced autocorrelation vector 152.

R can be a block Topelitz matrix where its Ri,j Topelitz block is thecovariance built from a cross-correlation vector r_(i,j), whereinr_(i,j)=F^(H) _(D,N)*diag(F_(N,N)x_(i))*F_(N,N)x_(i)″. Thecross-correlation vector r_(i,j), can be calculated by performing acircular convolution between x_(i) and x_(i)″: r_(i,j)=F^(H)_(D,N)*diag(F_(N,N)x_(i))*(F_(N,N)x_(j))*.

If there are four diversity branches (B0, B1, B2 and B3) then R shouldinclude 16 blocks (matrixes) that represent 16 different correlationsbetween these diversity branches. The indecies of each of the blocks(matrices) that form R indicate the diversity branches that arecorrelated to form these matrixes.

R can have the following format:

$R = \begin{pmatrix}R_{0,0} & R_{0,1} & R_{0,2} & R_{0,3} \\R_{1,0} & R_{1,1} & R_{1,2} & R_{1,3} \\R_{2,0} & R_{2,1} & R_{2,2} & R_{2,3} \\R_{3,0} & R_{3,1} & R_{3,2} & R_{3,3}\end{pmatrix}$

Because R is a block Topelitz matrix then R_(i,j)=R_(j,i) ^(H). When Rincludes 4×4 blocks (matrices) then there is no need to calculate theentire sixteen matrices—only 10 can be calculated.

Because of the anti-aliasing filtering, some of these matrices areredundant—or can be ignored without significant loss of performance.Thus, the First calculation unit 51 can calculate only matrices R_(0,0),R_(0,2) and R_(2,2).

If the delay spread of the input signals is less that 32 chips, theneach matrix out of R_(0,0), R_(0,2) and R_(2,2) should include 32columns and 32 rows.

Because each of R_(0,0), R_(0,2) and R_(2,2) is a Topelitz matrix (amatrix in which each descending diagonal from left to right is constant)then each matrix can be represented by a vector of 63 elements—as thenumber of descending diagonals in the matrix.

A small constant can be added to the diagonal of R (by the firstcalculation unit 51) in order to improve its numerical stability.

The second calculation unit 52 includes a multiplier 522 that isfollowed by an IFFT unit 524 and a pilot storage unit 526. The pilotstorage unit 526 stores a pilot sequence 154. The multiplier 522 can bepreceded by an FFT unit that performs an FFT conversion on a pilotsequence.

The second calculation unit 52 calculates the symbol spaced channelestimation 156. The symbol spaced channel estimation 156 is representedby vector g.

g=[g ₁ ^(T) . . . g _(L) ^(T)],wherein: g _(j) =F ^(H) _(D,N)*diag(F_(N,N) p)*(F _(N,N) x _(j))*.

The interpolation unit 54 receives the symbol spaced autocorrelation 152and interpolates it to provide the fractionally spaced autocorrelation162.

Assuming that r_(ij) is provided by the first calculation unit 51 thenr_(2k,2l+1) is interpolated by: r_(2k,2l+1)=r_(ij)*w and r_(2k+1,2l+1)is interpolated by: r_(2k+1,2l+1)=r_(ij)*w′.

The interpolation unit 54 also receives the symbol spaced channelestimation 156 and interpolates it to provide the fractionally spacedchannel estimation 166. Assuming that g_(2k) is provided by the secondcalculation unit 52, then g_(2k+1) is interpolated by:g_(2k+1)=g_(2k)*w.

The third calculation unit 53 includes: (i) averaging units such asInfinite Impulse Response (IIR) filters 531 and 532, (ii) a circulantextension unit 533, and (iii) a normal equation solver 534.

The circulant extension unit 533 is connected between the IIR filter 531and the normal equation solver 534 and is arranged to process R.

The IIR filter 532 is connected between the interpolation unit 54 andthe normal equation solver 534 and is arranged to filter g.

The IIR filter 531 averages R. The averaging can be applied on R resultsobtained from consecutive blocks of symbol spaced samples. The taps 168of the fractionally spaced equalizer 60 are calculated per each block ofsymbol spaced symbols so that the averaging can take into accountresults from the previous calculation of such taps.

The IIR filter 532 averages vector g. The averaging can be applied on gresults obtained from the consecutive blocks of the symbol spacessamples.

In order to diagonalize the autocorrelation matrix using FFT, theaveraged R matrix should be a block circulant. The circulant extensionunit 533 can achieve this goal by replacing each of (the averaged) blockRij by its circular approximation Cij. It is noted that the receiver 10′can also include an extending unit (not shown) for extending g toprovide q, q=[g^(T)*o^(T) _(DL)]^(T). O is the zero matrix.

The normal equation solver 534 outputs the taps 168 of the fractionallyspaced equalizer 60. The process applied by the normal equation solver534 starts by diagonalizing each sub-block Cij in C by calculating thefollowing:

_(ij)=F_(2D,2D)*C_(i,j)*F^(H) _(2D,2D). It is noted that C can equal(I_(L)ΘF^(H) _(2D,2D))*

*(I_(L)ΘF_(2D,D)). In this case f can equal (I_(L)ΘF^(H) _(2D,2D))*

⁻¹*(I_(L)Θ*F_(2D,D))*q. I_(L) is an m×m identity matrix.

These diagonalizing operations of the normal equation solver 534 areexecuted by the FFT unit 535, the FFT unit 536, the matrix inversionunit 537, the multiplier 538 and the IFFT unit 539.

The FFT unit 535 is connected between the circular extension unit 533and the matrix inversion unit 537. The FFT unit 536 is connected betweenthe IIR filter 532 and the multiplier 538. The Multiplexer 538 is alsoconnected to the IFFT unit 539 and to the circular extension unit 533.The IFFT unit 539 is connected to the fractionally spaced filter 60.

The fractionally spaced equalizer 60 receives the taps 168 and performsan FFT transform (by a FFT unit 61) to provide frequency domain taps169. The frequency domain taps 169 are multiplied (by the multiplier 62)by the fractionally spaced samples 130 and 130′ to provide products thatare sent to the adder 63. The adder 63 adds each product to previoussums. The output of the adder 63 is connected to the IFFT unit 64 thatoutputs the equalized signals 170.

$\quad\left\{ \begin{matrix}{{x_{1\;}^{2X}(m)},{m = 0},1,\ldots \mspace{14mu},{{2N} + 1}} \\{{x_{2}^{2X}(m)},{m = 0},1,\ldots \mspace{14mu},{{2N} + 1}}\end{matrix} \right.$

The input signals 110 and 110′ can be represented by the followingequations:

$\quad\left\{ \begin{matrix}{{{x_{1}(n)} = {x_{1}^{2X}\left( {2n} \right)}},{n = 0},1,\ldots \mspace{14mu},N} \\{{{x_{2}(n)} = {x_{1}^{2X}\left( {{2n} + 1} \right)}},{n = 0},1,\ldots \mspace{14mu},N} \\{{{x_{3}(n)} = {x_{2}^{2X}\left( {2n} \right)}},{n = 0},1,\ldots \mspace{14mu},N} \\{{{x_{4}(n)} = {x_{2}^{2X}\left( {{2n} + 1} \right)}},{n = 0},1,\ldots \mspace{14mu},N}\end{matrix} \right.$

After an oversampling with an oversampling ratio of two the followingdiversity branches are provided:

$R_{k} = \begin{bmatrix}{r_{11}(k)} & {r_{12}(k)} & {r_{13}(k)} & {r_{14}(k)} \\{r_{21}(k)} & {r_{22}(k)} & {r_{23}(k)} & {r_{24}(k)} \\{r_{31}(k)} & {r_{32}(k)} & {r_{33}(k)} & {r_{34}(k)} \\{r_{41}(k)} & {r_{42}(k)} & {r_{43}(k)} & {r_{44}(k)}\end{bmatrix}$

The auto-correlation and cross-correlation can be expressed by thefollowing equations:

$R_{k} = \begin{bmatrix}{r_{11}(k)} & {\frac{1}{2}\left\lbrack {{r_{11}(k)} + {r_{11}(k)}} \right\rbrack} & {r_{13}(k)} & {\frac{1}{2}\left\lbrack {{r_{13}(k)} + {r_{13}\left( {k + 1} \right)}} \right\rbrack} \\{\frac{1}{2}\left\lbrack {{r_{11}(k)} + {r_{11}\left( {k - 1} \right)}} \right\rbrack} & {r_{11}(k)} & {\frac{1}{2}\left\lbrack {{r_{13}(k)} + {r_{13}\left( {k - 1} \right)}} \right\rbrack} & {r_{13}(k)} \\{r_{31}(k)} & {\frac{1}{2}\left\lbrack {{r_{31}(k)} + {r_{31}\left( {k + 1} \right)}} \right\rbrack} & {r_{33}(k)} & {\frac{1}{2}\left\lbrack {{r_{33}(k)} + {r_{33}\left( {k + 1} \right)}} \right\rbrack} \\{\frac{1}{2}\left\lbrack {{r_{31}(k)} + {r_{31}\left( {k - 1} \right)}} \right\rbrack} & {r_{31}(k)} & {\frac{1}{2}\left\lbrack {{r_{33}(k)} + {r_{33}\left( {k - 1} \right)}} \right\rbrack} & {r_{33}(k)}\end{bmatrix}$

Wherein

$\quad\left\{ \begin{matrix}{{r_{11}(k)} = {\sum\limits_{n}{{x_{1}(n)}{x_{1}^{*}\left( {n + k} \right)}}}} \\{{r_{13}(k)} = {{\sum\limits_{n}{{x_{1}(n)}{x_{3}^{*}\left( {n + k} \right)}}} = {r_{31}^{*}\left( {- k} \right)}}} \\{{r_{33}(k)} = {\sum\limits_{n}{{x_{3}(n)}{x_{3}^{*}\left( {n + k} \right)}}}}\end{matrix} \right.$

FIG. 4 schematically shows a flow-chart of an example of a method 400for equalizing signals.

The illustrated method 400 includes stages 410, 420, 430, 440, 450 and460 and may for example be performed with the receiver of FIG. 1 or 2.

Stage 410 includes receiving one or more input signals. An input signalcan include a sequence of electromagnetic pulses or waveforms that arereceived by an input antenna. An input antenna is an antenna thatreceives electromagnetic radiation.

Stage 410 can, for example, be executed by a radio frequency (RF)front-end of a receiver. The receiver can be included in a cell phone,media player, computer and the like.

Stage 410 can, for example, include receiving input signals frommultiple input antennas. The multiple antennas can receive(substantially simultaneously) the same (or substantially the same)transmitted electromagnetic pulses or waveforms.

Stage 420 includes generating oversampled samples. These oversampledsamples reflect the received one or more input signals. They can begenerated by oversampling the one or more input signals, filtering thesamples by an input filter and the like.

Stage 430 includes processing the oversampled samples to provide symbolspaced samples.

Stage 430 can, for example, include at least one of the following stagesor a combination thereof: (i) stage 431 of filtering the oversampledsamples by an input filter (such as a matched filter or a selectivityfilter) to provide filtered fractionally spaced samples, (ii) stage 434of anti-aliasing filtering of the filtered fractionally spaced samplesto provide anti-aliased filtered fractionally spaced samples, (iii)stage 436 of performing a time to frequency domain conversion on theanti-aliased filtered fractionally spaced samples to provide thefractionally spaced samples; and (iv) stage 438 of down-sampling thefractionally spaced samples to provide the symbol spaced symbols.

Stage 434 can include anti-aliasing filtering of the oversampled samplesto provide the fractionally spaced samples that represent theoversampled samples. Stage 434 can include applying an anti-aliasingfilter that has a time response that is substantially equal to a symbolperiod of the one or more input signal.

It is noted that stage 420 can include generating the oversampledsamples by an analog to digital converter and stage 434 can includeperforming the anti-aliasing filtering by an anti-aliasing filter thatis integrated with the analog to digital filter.

Stage 440 includes calculating taps of a fractionally spaced equalizerbased on the symbol spaced samples.

Stage 440 can include at least one of the following stages or acombination thereof: (i) stage 4410 of calculating a chip spacedautocorrelation of the symbol spaced samples; (ii) stage 4420 ofcalculating a symbol spaced channel estimation; (iii) stage 4430 ofinterpolating the symbol spaced autocorrelation and the symbol spacedchannel estimation to provide a fractionally spaced autocorrelation anda fractionally spaced channel estimation; and (iv) stage 4440 ofgenerating the fractionally spaced equalizer based on the fractionallyspaced autocorrelation and the fractionally spaced channel estimation.

Stage 445 includes feeding the taps to the fractionally spaced filter.

Stage 450 includes filtering fractionally spaced samples that representthe oversampled samples by the fractionally spaced equalizer to provideequalized signals. The filtering is executed by a fractionally spacedfilter that was fed with taps that were calculated during stage 440.Stage 440 can, for example, include calculating a fractionally spacedequalizer that is a half symbol spaced equalizer.

Stage 460 includes processing the equalized samples. This stage caninclude filtering, decoding, displaying images based on the samples,playing music based on the samples and the like.

FIGS. 5, 6 and 7 schematically show examples of graphs that illustratethe results of simulations that evaluated different equalizationalgorithms.

FIG. 5 illustrates the signal to noise ratio (SNR) versus throughput fora fractionally spaced equalizer (graph 510), a symbol spaced equalizer(graph 530) and an improved equalizer (graph 520) such as the equalizerof FIG. 2 for a flat channel profile.

It can be easily seen that the performance of the improved equalizer wassubstantially the same as the fractionally spaced equalizer and that theperformance of the symbol spaced equalizer were lower in relation to theperformance of the other equalizers.

FIG. 6 illustrates the signal to noise ratio (SNR) versus throughput fora fractionally spaced equalizer, a symbol spaced equalizer and animproved equalizer for a pedestrian B channel profile.

It can be easily seen that the performance of the improved equalizer(graph 610), was better than the performance of the symbol spacedequalizer (graph 630), and was slightly lower than the performance ofthe fractionally spaced equalizer (graph 620).

FIG. 7 illustrates the SNR versus throughput for a fractionally spacedequalizer, a symbol spaced equalizer and an improved equalizer for avehicle A channel profile.

It can be easily seen the performance of the improved equalizer (graph710), was better than the performance of the symbol spaced equalizer(graph 730), and was slightly lower than the performance of thefractionally spaced equalizer (graph 710),

The complexity of the improved equalizer (such as the equalizer of FIG.2) was compared to the complexity of a fractionally spaced equalizer anda symbol spaced equalizer. The complexity (represented by the number ofcalculations required for calculating the taps of the equalizer) of theimproved equalizer was 661 calculations, the complexity of the symbolspaced equalizer was 463 calculations and the complexity of thefractionally spaced equalizer was 1122 calculations. This complexity wasobtained by performing frequency domain calculations (that required FFTtransforms). It is noted that when performing time domain calculationsthe fractionally spaced equalizer required 2458 calculations.

These calculations were simulated under the following assumptions: thereceiver has two input antennas, an oversampling ratio of 2, a channelsdelay spread shorter than 32 chips, the tap calculation is executed each1280 chips on a block of 1536 chips, the equalizer uses 32 taps in timedomain per diversity branch and 64 taps in frequency domain perdiversity branch.

Those skilled in the art will recognize that the boundaries betweenlogic blocks are merely illustrative and that alternative embodimentscan merge logic blocks or circuit elements or impose an alternatedecomposition of functionality upon various logic blocks or circuitelements. Thus, it is to be understood that the architectures depictedherein are merely exemplary, and that in fact many other architecturescan be implemented which achieve the same functionality. For example,the calculator can calculate the taps without diagonalizing matrixes.Yet for another example, the taps can be calculated in the time domaininstead of the frequency domain and thus the FFT units and IFFT unitsillustrated in FIGS. 1, 2 and 3 can be removed. Yet for a furtherexample, the descrambling/de-spreading filter can precede thefractionally spaced equalizer.

Any arrangement of components to achieve the same functionality iseffectively “associated” such that the desired functionality isachieved. Hence, any two components herein combined to achieve aparticular functionality can be seen as “associated with” each othersuch that the desired functionality is achieved, irrespective ofarchitectures or intermedial components. Likewise, any two components soassociated can also be viewed as being “operably connected,” or“operably coupled,” to each other to achieve the desired functionality.

Furthermore, those skilled in the art will recognize that boundariesbetween the above described operations merely illustrative. The multipleoperations can be combined into a single operation, a single operationcan be distributed in additional operations and operations can beexecuted at least partially overlapping in time. Moreover, alternativeembodiments can include multiple instances of a particular operation,and the order of operations can be altered in various other embodiments.

Also for example, in one embodiment, the illustrated examples can beimplemented as circuitry located on a single integrated circuit orwithin a same device. For example, an analog to digital converter andthe interpolation unit can be located on a single system on chip.Alternatively, the examples can be implemented as any number of separateintegrated circuits or separate devices interconnected with each otherin a suitable manner. For example, an analog to digital converter andthe interpolation unit can be located on different integrated circuits.

Also for example, the examples, or portions thereof, can implemented assoft or code representations of physical circuitry or of logicalrepresentations convertible into physical circuitry, such as in ahardware description language of any appropriate type.

Also, the invention is not limited to physical devices or unitsimplemented in non-programmable hardware but can also be applied inprogrammable devices or units able to perform the desired devicefunctions by operating in accordance with suitable program code, such ascell phones, base stations, personal computers, media players personaldigital assistants, electronic games, automotive and other embeddedsystems, and various other wireless devices, commonly denoted in thisapplication as ‘computer systems’.

However, other modifications, variations and alternatives are alsopossible. The specifications and drawings are, accordingly, to beregarded in an illustrative rather than in a restrictive sense.

In the claims, any reference signs placed between parentheses shall notbe construed as limiting the claim. The word ‘comprising’ does notexclude the presence of other elements or steps then those listed in aclaim. Furthermore, the terms “a” or “an,” as used herein, are definedas one or more than one. Also, the use of introductory phrases such as“at least one” and “one or more” in the claims should not be construedto imply that the introduction of another claim element by theindefinite articles “a” or “an” limits any particular claim containingsuch introduced claim element to inventions containing only one suchelement, even when the same claim includes the introductory phrases “oneor more” or “at least one” and indefinite articles such as “a” or “an.”The same holds true for the use of definite articles. Unless statedotherwise, terms such as “first” and “second” are used to arbitrarilydistinguish between the elements such terms describe. Thus, these termsare not necessarily intended to indicate temporal or otherprioritization of such elements. The mere fact that certain measures arerecited in mutually different claims does not indicate that acombination of these measures cannot be used to advantage.

1. A method for equalizing signals, the method comprises: receivinginput signals; sampling the input signals to provide oversampledsamples; processing the oversampled samples to provide symbol spacedsamples and to provide fractionally spaced samples that represent theoversampled samples; calculating taps of a fractionally spaced equalizerbased on the symbol spaced samples; feeding the taps to the fractionallyspaced equalizer; and filtering the fractionally spaced samples by thefractionally spaced equalizer to provide equalized samples.
 2. Themethod according to claim 1, comprising calculating the taps of afractionally spaced equalizer that is a half symbol spaced equalizer. 3.The method according to claim 1, comprising processing the oversampledsamples without applying anti-aliasing filtering.
 4. The methodaccording to claim 1, comprising: calculating a symbol spacedautocorrelation of the symbol spaced samples; calculating a symbolspaced channel estimation; interpolating the symbol spacedautocorrelation and the symbol spaced channel estimation to provide afractionally spaced autocorrelation and a fractionally spaced channelestimation; and calculating the taps of the fractionally spacedequalizer based on the fractionally spaced autocorrelation and thefractionally spaced channel estimation.
 5. The method according to claim1, comprising: receiving a transmitted signal by multiple antennas toprovide multiple input signals; and sampling the multiple input signalsto provide the oversampled samples.
 6. The method according to claim 1,comprising anti-aliasing filtering of the oversampled samples to providefractionally spaced samples that represent the oversampled samples. 7.The method according to claim 6, comprising applying an anti-aliasingfilter that has a time response that is substantially equal to a symbolperiod of an input signal that is represented by the oversampledsamples.
 8. The method according to claim 6, comprising: calculating asymbol spaced autocorrelation of the symbol spaced samples; calculatinga symbol spaced channel estimation; interpolating the symbol spacedautocorrelation and the symbol spaced channel estimation to provide afractionally spaced autocorrelation and a fractionally spaced channelestimation; and calculating the taps of the fractionally spacedequalizer based on the fractionally spaced autocorrelation and thefractionally spaced channel estimation.
 9. The method according to claim6, comprising: generating the oversampled samples by an analog todigital converter; and performing the anti-aliasing filtering by ananti-aliasing filter that is integrated with the analog to digitalconverter.
 10. A receiver, comprising: a sampling unit, for samplinginput signals to provide oversampled samples; a processing unit, coupledto the sampling unit, for processing the oversampled samples to providesymbol spaced samples and to provide fractionally spaced samples; afractionally spaced equalizer, coupled to the processing unit, forfiltering the fractionally spaced samples to provide equalized samples;and a calculator for calculating taps of the fractionally spacedequalizer based on the symbol spaced samples and for feeding the taps tothe fractionally spaced equalizer.
 11. The receiver according to claim10, wherein the fractionally spaced equalizer is a half symbol spacedequalizer.
 12. The receiver according to claim 10, wherein processingunit is arranged to process the oversampled samples without applyinganti-aliasing filtering.
 13. The receiver according to claim 10, whereinthe calculator comprises: a first calculation unit for calculating asymbol spaced autocorrelation of the symbol spaced samples; a secondcalculation unit for calculating a symbol spaced channel estimation; aninterpolation unit for interpolating the symbol spaced autocorrelationand interpolating the symbol spaced channel estimation to provide afractionally spaced autocorrelation and a fractionally spaced channelestimation; and a third calculation unit for calculating the taps of thefractionally spaced equalizer based on the fractionally spacedautocorrelation and the fractionally spaced channel estimation.
 14. Thereceiver according to claim 10, comprising: multiple input antennas forreceiving a transmitted signal to provide multiple input signals; andsampling units for sampling the multiple input signals to provide theoversampled samples.
 15. The receiver according to claim 10, wherein theprocessing unit comprises an anti-aliasing filter for anti-aliasingfiltering of the oversampled samples to provide the fractionally spacedsamples.
 16. The receiver according to claim 15, wherein theanti-aliasing filter has a time response that is substantially equal toa symbol period of an input signal that is represented by theoversampled samples.
 17. The receiver according to claim 15, wherein thecalculation unit comprises: a first calculation unit for calculating asymbol spaced autocorrelation of the symbol spaced samples; a secondcalculation unit for calculating a symbol spaced channel estimation; aninterpolation unit for interpolating the symbol spaced autocorrelationand interpolating the symbol spaced channel estimation to provide afractionally spaced autocorrelation and a fractionally spaced channelestimation; and a third calculation unit for calculating thefractionally spaced equalizer based on the fractionally spacedautocorrelation and the fractionally spaced channel estimation.
 18. Thereceiver according to claim 15, wherein the sampling unit is an analogto digital converter, and wherein the anti-aliasing filter is integratedwith the analog to digital converter.
 19. The method according to claim2, comprising: receiving a transmitted signal by multiple antennas toprovide multiple input signals; and sampling the multiple input signalsto provide the oversampled samples.
 20. The receiver according to claim11, wherein the calculator comprises: a first calculation unit forcalculating a symbol spaced autocorrelation of the symbol spacedsamples; a second calculation unit for calculating a symbol spacedchannel estimation; an interpolation unit for interpolating the symbolspaced autocorrelation and interpolating the symbol spaced channelestimation to provide a fractionally spaced autocorrelation and afractionally spaced channel estimation; and a third calculation unit forcalculating the taps of the fractionally spaced equalizer based on thefractionally spaced autocorrelation and the fractionally spaced channelestimation.